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基于互信息的图像相似性测量。Image similarity using mutual information of regions .pdf
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mutual information medical image match
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很全的图像融合指标，综合熵、空间频率、互信息等等，一共7种！和两幅源图像！每个程序都测试过，效果很好，直接出结果,Are all indicators of image fusion, integrated entropy, spatial frequency, mutual information, etc., a total of 7! And the two source image! Each program is tested with good results, directly r
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使用互信息进行2D图像自动配准源代码,应用平均互信息,The use of mutual information for automatic registration 2D image source code, the application of the average mutual information
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基于最大互信息的图像配准算法源程序
用matlab编写的-Based on the maximum mutual information image registration algorithm using matlab source prepared
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提出了一种优化的图像配准算法。首先把图像中的兴趣点及其角度信息提取出来，利用互信息准则，得到需要的配对点，得到两幅或多幅图像的拼接自然的完整图像, 实验表明，该算法是有效的。-An optimized image registration algorithm. First of all, the image of interest points and their point of view of information extracted, using the criteria of mutu
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图象配准源程序一，
GUI界面，proj.m
图片选择窗口，testListBoxlj.m
二,最优化算法
PSO.m
POWELL.m
三，互信息尺度
MI.m
EMI.m
RMI.m
HiMI.m
GMI.m
FPMI.m
四，POWELL.m附属子程序
oneDimSearch.m
五，PSO.m附属子程序
myMI.m
六，配准结果检验程序
restore.m
七，
gob
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The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all
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-The existence of numerous imaging modalities makes it possible to present different data present in different modalities together thus forming multimodal images. Component images forming multimodal images should be aligned, or registered so that all
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一种新的方法，可以自动对两幅图像进行刚性配准。采用matlab和c++混编，速度得到一定的提高。-Rigid body 2-D image co-registration (translation and rotation) is performed using maximization of mutual information.
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本文针对多光谱图像配准中不同光谱图像间存在较大的灰度差异、同一景
物在不同波段表现的特征也各不相同等问题，提出了基于互信息相似性测度的
多光谱图像配准算法。-In this paper, multi-spectral image registration between images in different spectral gray there is a big difference, the same scene in different performance character
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基于互信息的图像配准算法，优化算法采用Powell和粒子群向结合的算法-Based on mutual information image registration algorithm, using Powell optimization algorithm and particle swarm algorithm to combine
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Image Registration by Mutual Information
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图像配准中的两幅图像的归一化互信息计算方法代码-Image registration of two images of the normalized mutual information method code
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图像融合指标，综合熵、空间频率、互信息等等，一共7种。在图像处理后的质量评价方面很有用-Fusion index, comprehensive entropy, spatial frequency, mutual information, etc., a total of 7 species. In the image processing is useful for quality assessment
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a fuction calculates the entropy for a image: ientropy.m
a fonction calculates the joint entropy bethwin too images: jentropy.m
à fuction calculates the mutual information bithwin too images imf.m
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lena图像互信息求取，包括各个颜色值之间的互信息求取，运行通过！-lena image to strike a mutual information, including all the mutual information between the color values to strike, to run through!
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红外和可见光的匹配跟踪在军事、遥感等领域有着广泛的应用。针对灰度和图像特征存在比较大差异的红外和可见光图像，本文采用了最大互信息算法，结合形态学梯度和小波分解。互信息算法优点在于不需要对多模图像灰度间的关系做任何假设，不足之处在于它对图像空间信息的忽略而且计算时间较长。本文互信息结合多结构元的形态学梯度检测的图像边缘，可以使得图像匹配精度提高，还能改善局部极值的问题，再利用小波分解对图像进行压缩降低分辨率，可以减少互信息计算量。最后的实验数据表明在配准过程中互信息的计算速度得到了优化，匹配精度得
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用互信息方法做的图像配准，效果很好，不足就是运行时间太长-Image registration operated by mutual information method works well, the lack of it is that running time is too long.
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关于计算两幅图像的互信息，对配准有一定作用-On computing the mutual information of two image, is a role for registration
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